Predictive Analytics From The Bench

How Predictive Analytics Plays out in Baseball (And Marketing)

The 2013 baseball season is coming to a close, and if you’re a fan of baseball and data analytics, you have to be pretty pleased with how the fall classic has been playing out. Here in the Boston offices of Lattice Engines, there has been a lot to root for. No doubt our beloved Red Sox and their play has been the focus of constant talk around the coffee maker in the morning. Bleary eyed developers, marketers and product folks are staying up late to catch the action and see if the Sox can pull off another victory in this “worst to first” season.

But, with our recent launch of our predictive marketing application, it gives us data geeks a whole new appreciation for October baseball. Sure, we’ve all heard of Moneyball by this point and Billy Beane’s approach to building up a successful baseball team by managing statistics and payroll. But if you’re the manager of a World Series team, and you’re in the thick of a playoff run, how do you manage your players – by gut feeling or by playing the percentages?

GUT-FEEL VS MONEYBALL

Before Predictive Lead Scoring, many marketers were managing leads by gut feeling like old time baseball managers. A good trade show must produce good leads. A contact downloading a white paper and spending more than 30 seconds on a page had to be a good lead. Sometimes baseball managers make decisions based on their feeling for the moment. Sometimes it works, and sometimes it doesn’t. Whether it does or not usually depends on the player, not the manager.

For example, in Game 2 of the World Series, Red Sox DH David Ortiz came to the plate with his team down 1-0 and St. Louis’ stud pitcher Michael Wacha was ready to go. While only game 2 of the Series, Ortiz already had a home run in game 1 and had been hitting well in the World Series so far. The Cardinals’ manager Mike Matheny decided to let Wacha pitch to Ortiz, even though he had already cautiously walked Ortiz that evening. Matheny’s “gut” told him that Wacha could pitch to him. Instead, Ortiz drove it out of the park to give his team a temporary lead.

In sales and marketing, this is often when marketing delivers a batch of “hot” leads and leaves it to sales to convert them. Perhaps there are a few rainmakers in the sales group that can convert any lead, but is that really credit to the marketing group? Or are they just hopeful that the sales team will continue to perform well enough to win? In Matheny’s case, he was playing what he thought was the right move and not what the numbers told him he should probably do.

In game 5 of the World Series, we saw Red Sox manager John Farrell perform some fairly complicated line-up reshuffling, due potentially in part to some great analytics work. With 19 wins in the regular season and two in the post season so far, St. Louis pitcher Adam Wainwright was proving to be the big ace that St. Louis fans knew and loved. However, statistics showed that in the first inning of games, Wainwright seemed vulnerable. In fact, according to baseball-reference.com, opponents had a higher batting average against Wainwright in the first inning than in all other innings. In fact, of the 15 home runs he gave up all season a third were during the first inning. For Farrell and the Red Sox, this meant they had to get to Wainwright early and preferably within the first 3 outs! Farrell altered the top 3 order of the line-up, albeit slightly, to give his team the best opportunity to succeed. Instead of Ortiz batting 4th in the batting order, he was moved to 3rd. While this may not be a big change on the surface, consider that Ortiz had batted 4th in every post-season game to this point and in over 89% of regular games. Playing the analytics worked for Farrell and the Red Sox as Ortiz was able to get an RBI in his first at bat and give the Sox an early lead in a game where they eventually won.

PLAYING FOR SUCCESS

In this instance, Farrell managed the way that Lattice’s Predictive Lead Scoring manages leads for marketers. By applying analytics and assigning probabilities to succeed, Lattice allows marketers to put their salespeople in a better position to score big. Through data obtained from the marketer’s own systems, combined with the Lattice Data Cloud, marketers have insight into conversion rates that actually help them differentiate between those leads that have a high probability to close versus those that may appear from a great source, but should probably be best sent through a round or two of nurturing before passing to sales.

At Lattice, our Boston office hopes our Red Sox come through in one more game. We also hope that the benefits of predictive analytics can help you and your marketing team to score big!